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How do statistical methods shape what we know about the health effects of air pollution—and even what levels are considered “safe”? Join Michael Cork, MPH, PhD Candidate at the Harvard T.H. Chan School of Public Health, for an accessible, policy-relevant online seminar on estimating exposure–response relationships between pollution and health outcomes. Designed for PhD students and professional researchers, the session will introduce exposure–response curves, causal inference concepts such as confounding, exchangeability, and weighting, and compare these with traditional regression-based approaches. Drawing on recent JRSS-A research, including large-scale simulations and real-world air-pollution analyses using Medicare data, the seminar will show how different methods can lead to different public-health conclusions. While the examples focus on air pollution, the ideas apply broadly to continuous environmental exposures such as temperature, noise, and chemical pollutants. Participants will gain practical guidance on interpreting ERC methods, understanding assumptions and uncertainty, and recognizing how methodological choices influence risk estimates and policy standards. Live via Zoom, with recordings and materials available for 30 days, plus shared R-based examples and reproducible scripts for further exploration. #Biostatistics #DataScience #EnvironmentalSciences #PublicPolicy #Statistics #Epidemiology #PublicHealth #RStudio #R #Research #ResearchTraining #Instats